Publications
NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.
2025
Authors
Katrine Marie Brynildsrud Peter Horvath Michael Angeloff Wenche Dramstad Adam Eindride Naas Kerstin Potthoff Anders BrynAbstract
Expanding cities and urban densification is one of the major threats to biodiversity, ecosystem services and human welfare. Using Oslo, the capital city of Norway, as a case study this study addresses the following questions: (i) What vegetation changes have occurred between 1980s and 2021 and to what extent? (ii) What are the potential consequences of documented changes for biodiversity and other functions of green spaces? (iii) What future direction is the present development plan aiming for? To answer these questions, detailed vegetation maps (1:10 000) of Oslo from around 1980s were remapped in situ in 2021. We present results on land cover transformations, area statistics, and analyses of ecological impacts using landscape metrics. Our results document that large areas previously covered by vegetation types and cultivated land have been lost to urban densification. Housing dominated the new use. This loss of areas with vegetation types will affect ecosystem diversity negatively. On average, the total area and the mean patch area of each vegetation type decreased, whereas the mean Euclidean nearest-neighbor distance increased. These changes have lowered connectivity and increased fragmentation. Despite explicitly stated aims, previous efforts to reduce loss of areas with high biodiversity and maintain urban green spaces have not succeeded, and the planned future urban development indicates that a further decrease will follow in the next decades.
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Authors
Anne B. NilsenAbstract
NIBIO produces Green Structure Maps (GSM) for Norway that cover built-up areas, including cabin areas. GSM is a hybrid product based on information from remote sensing data and detailed national vector datasets such as roads, water, buildings, and land use. GSM contains 8 classes: Ground, Shrub, Tree, Grey, Road, Water, Building, and Agriculture. QGIS is excellently suited for visual control of GSM. Based on the size of the dataset (number of polygons), a significant random sample of each class is selected to check whether it is correctly classified. You can organize the map layers into different themes, set up QGIS with multiple map windows showing different themes and zoom levels, and use existing plugins to jump from polygon to polygon and compare with aerial images and code whether the classification is correct or not - quickly and efficiently. More comprehensive statistics can then be calculated, and the results can be compared against the requirements to determine if the GSM meets the standards.
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Urban agriculture (UA) is increasingly recognized as a key component of sustainable cities. Commercial farmers in urban areas benefit from a large customer base, short transport distances, and access to diverse sales channels. However, high pressure on land resources makes it difficult for farmers and decision makers to find suitable areas for UA. This study ranks urban and peri-urban farmland areas based on their suitability for urban agriculture (UA) and identifies opportunities for extending the area for UA to currently unused farmland. Through collaboration with urban farmers, we identified four key themes and eleven criteria, which were weighted for two sales scenarios: on-farm and off-farm. We performed a GIS-based multi-criteria decision analysis (MCDA) and assessed suitability using the technique of order preference similarity to the ideal solution (TOPSIS) on 1 × 1 km grid cells. By overlaying the suitability maps with presumably unused farmland (PUF), we identified areas with high potential for extending UA. In the City of Bergen, 15.3 % (on-farm; off-farm=14 %) of the total farmland is both unused and highly suitable for UA, compared to only 2.8 % (on-farm; off-farm=2.4 %) in Oslo. Assessing the suitability of agricultural land for UA can support spatial planning, protect agricultural topsoil from urban expansion, and help achieve global, national, and local goals for urban farming and sustainable land use.
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Many countries have goals to reduce soil sealing of agricultural land to preserve food production capacity. To monitor progress, reliable data are needed to quantify soil sealing and changes over time. We examined the potential of the Imperviousness Classified Change (IMCC) 2015–2018 product provided by the Copernicus Land Monitoring Service (CLMS) to assess soil sealing in agricultural areas in Poland and Norway. We found very high overall accuracy due to the dominance of the area with no change. When we focused on areas classified as change, we found low user accuracy, with over-estimation of soil sealing. The producer accuracy was generally much higher, meaning that real cases of soil sealing were captured. This is better than under-estimation of soil sealing because it highlights areas where sealing may have occurred, allowing the user to carry out further control of this much smaller area, without having to assess the great expanse of unchanged area. We concluded that the datasets provide useful information for Europe. They are standardized and comparable across countries, which can enable comparison of the effects of policies intended to prevent soil sealing. Some distinctions between classes are not reliable, but the general information about increase or decrease is useful.
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No abstract has been registered